Tag Computer Vision and Pattern Recognition
Crowd segmentation is an important task in computer vision that aims to separate individuals or objects from crowded scenes. This task has numerous applications, including crowd monitoring, behavior analysis, and security surveillance. In recent years, deep learning has revolutionized the… Continue Reading →
How can we accurately predict the depth of a 3D scene using only a single image? This question has intrigued researchers for a long time, as depth estimation plays a crucial role in understanding the geometry of a scene. While… Continue Reading →
In the world of computer vision and artificial intelligence, the Microsoft COCO (Common Objects in Context) dataset has emerged as a valuable resource for advancing the state-of-the-art in object recognition and scene understanding. With the aim of providing a comprehensive… Continue Reading →
The Support Vector Machine (SVM) is a widely recognized and highly successful approach in the field of pattern recognition and machine learning. However, it has its limitations, one of which is its inability to generate predictive distributions. In this article,… Continue Reading →
Have you ever gazed up at the night sky and marveled at the moon’s mysterious ability to appear larger near the horizon than when it’s high above? This optical illusion, aptly named the moon illusion, has puzzled scientists and stargazers… Continue Reading →
Distortion in digital cameras is a common issue that affects the accuracy and quality of photographs. Addressing this problem, a research paper titled “High-precision camera distortion measurements with a calibration harp” presents a novel approach to measuring distortion in digital… Continue Reading →
Trans-national migration has become a global phenomenon in recent years, impacting a growing number of individuals around the world. Many of these migrants have already attained higher education degrees in their home countries or previous residences prior to migrating. As… Continue Reading →